Poetry Generation via Deep Neural Networks

Natural language generation is one of the many problems that computer linguistics addresses. Different types of generation include generating CVs, weather forecasts, dialogues, or creative texts such as stories, jokes, and poetry. In recent years, the generation of poetry has become an interesting problem in the research field. Poetry uses various creative features compared to other texts, taking into account phonetics, lexicology, syntax, and requires a lot of input information. Although there are several evaluation metrics, they are ambiguous and there is a problem in correlation with human evaluation. Especially Chinese poems are widespread among researchers, and the English language lags far behind.

We will analyze the existing approaches, methods, and architectures that are used to generate poetry today. We will suggest the new one or improve an already existing method for generating poetry using deep neural networks for English language. Then we will implement the solution and compare the results with existing approaches.